{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Bikeshare数据集上的数据探索\n",
    "\n",
    "1、任务描述\n",
    "请在Capital Bikeshare（美国的一个共享单车公司）提供的自行车数据上进行回归分析。根据每天的天气信息，预测该天的单车骑行量。\n",
    "\n",
    "1)应用文件\n",
    "day.csv:按天计的单车共享次数\n",
    "2）字段说明\n",
    "Instant:记录号\n",
    "Dteday:日期\n",
    "Season:季节(1=春天，2=夏天，3=秋天，4=冬天)\n",
    "yr:年份(0:2011,1:2012)\n",
    "mnth：月份\n",
    "hr：小时\n",
    "holiday：是否为节日\n",
    "weekday：星期几\n",
    "workingday：是否为工作日\n",
    "weathersit：天气(1:晴天，多云；2：雾天，阴天；3：小雪，小雨；4：大雨，大雪，大雾)\n",
    "temp：气温摄氏度\n",
    "atemp：体感温度\n",
    "hum：湿度\n",
    "windspeed：风速\n",
    "casual：非注册用户个数\n",
    "registered：注册用户个数\n",
    "cnt：给定日期时间的总租车人数，响应变量y"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 导入必要工具包"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sn\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "\n",
    "#设置参数\n",
    "params = {\"legend.fontsize\":\"x-large\",\n",
    "          \"figure.figsize\":(30,10),\n",
    "          \"axes.labelsize\":\"x-large\",\n",
    "          \"axes.titlesize\":\"x-large\",\n",
    "          \"xtick.labelsize\":\"x-large\",\n",
    "          \"ytick.labelsize\":\"x-large\"\n",
    "}\n",
    "\n",
    "sn.set_style(\"whitegrid\")\n",
    "sn.set_context(\"talk\")\n",
    "\n",
    "plt.rcParams.update(params)\n",
    "pd.options.display.max_colwidth = 600\n",
    "\n",
    "#pandas数据显示\n",
    "from IPython.display import display,HTML"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instant</th>\n",
       "      <th>dteday</th>\n",
       "      <th>season</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>holiday</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.344167</td>\n",
       "      <td>0.363625</td>\n",
       "      <td>0.805833</td>\n",
       "      <td>0.160446</td>\n",
       "      <td>331</td>\n",
       "      <td>654</td>\n",
       "      <td>985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2011-01-02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.363478</td>\n",
       "      <td>0.353739</td>\n",
       "      <td>0.696087</td>\n",
       "      <td>0.248539</td>\n",
       "      <td>131</td>\n",
       "      <td>670</td>\n",
       "      <td>801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2011-01-03</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.196364</td>\n",
       "      <td>0.189405</td>\n",
       "      <td>0.437273</td>\n",
       "      <td>0.248309</td>\n",
       "      <td>120</td>\n",
       "      <td>1229</td>\n",
       "      <td>1349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2011-01-04</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.212122</td>\n",
       "      <td>0.590435</td>\n",
       "      <td>0.160296</td>\n",
       "      <td>108</td>\n",
       "      <td>1454</td>\n",
       "      <td>1562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2011-01-05</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.226957</td>\n",
       "      <td>0.229270</td>\n",
       "      <td>0.436957</td>\n",
       "      <td>0.186900</td>\n",
       "      <td>82</td>\n",
       "      <td>1518</td>\n",
       "      <td>1600</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   instant      dteday  season  yr  mnth  holiday  weekday  workingday  \\\n",
       "0        1  2011-01-01       1   0     1        0        6           0   \n",
       "1        2  2011-01-02       1   0     1        0        0           0   \n",
       "2        3  2011-01-03       1   0     1        0        1           1   \n",
       "3        4  2011-01-04       1   0     1        0        2           1   \n",
       "4        5  2011-01-05       1   0     1        0        3           1   \n",
       "\n",
       "   weathersit      temp     atemp       hum  windspeed  casual  registered  \\\n",
       "0           2  0.344167  0.363625  0.805833   0.160446     331         654   \n",
       "1           2  0.363478  0.353739  0.696087   0.248539     131         670   \n",
       "2           1  0.196364  0.189405  0.437273   0.248309     120        1229   \n",
       "3           1  0.200000  0.212122  0.590435   0.160296     108        1454   \n",
       "4           1  0.226957  0.229270  0.436957   0.186900      82        1518   \n",
       "\n",
       "    cnt  \n",
       "0   985  \n",
       "1   801  \n",
       "2  1349  \n",
       "3  1562  \n",
       "4  1600  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train = pd.read_csv(\"day.csv\")\n",
    "train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 731 entries, 0 to 730\n",
      "Data columns (total 16 columns):\n",
      "instant       731 non-null int64\n",
      "dteday        731 non-null object\n",
      "season        731 non-null int64\n",
      "yr            731 non-null int64\n",
      "mnth          731 non-null int64\n",
      "holiday       731 non-null int64\n",
      "weekday       731 non-null int64\n",
      "workingday    731 non-null int64\n",
      "weathersit    731 non-null int64\n",
      "temp          731 non-null float64\n",
      "atemp         731 non-null float64\n",
      "hum           731 non-null float64\n",
      "windspeed     731 non-null float64\n",
      "casual        731 non-null int64\n",
      "registered    731 non-null int64\n",
      "cnt           731 non-null int64\n",
      "dtypes: float64(4), int64(11), object(1)\n",
      "memory usage: 91.5+ KB\n"
     ]
    }
   ],
   "source": [
    "train.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instant</th>\n",
       "      <th>season</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>holiday</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>366.000000</td>\n",
       "      <td>2.496580</td>\n",
       "      <td>0.500684</td>\n",
       "      <td>6.519836</td>\n",
       "      <td>0.028728</td>\n",
       "      <td>2.997264</td>\n",
       "      <td>0.683995</td>\n",
       "      <td>1.395349</td>\n",
       "      <td>0.495385</td>\n",
       "      <td>0.474354</td>\n",
       "      <td>0.627894</td>\n",
       "      <td>0.190486</td>\n",
       "      <td>848.176471</td>\n",
       "      <td>3656.172367</td>\n",
       "      <td>4504.348837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>211.165812</td>\n",
       "      <td>1.110807</td>\n",
       "      <td>0.500342</td>\n",
       "      <td>3.451913</td>\n",
       "      <td>0.167155</td>\n",
       "      <td>2.004787</td>\n",
       "      <td>0.465233</td>\n",
       "      <td>0.544894</td>\n",
       "      <td>0.183051</td>\n",
       "      <td>0.162961</td>\n",
       "      <td>0.142429</td>\n",
       "      <td>0.077498</td>\n",
       "      <td>686.622488</td>\n",
       "      <td>1560.256377</td>\n",
       "      <td>1937.211452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.059130</td>\n",
       "      <td>0.079070</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.022392</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>22.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>183.500000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.337083</td>\n",
       "      <td>0.337842</td>\n",
       "      <td>0.520000</td>\n",
       "      <td>0.134950</td>\n",
       "      <td>315.500000</td>\n",
       "      <td>2497.000000</td>\n",
       "      <td>3152.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>366.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.498333</td>\n",
       "      <td>0.486733</td>\n",
       "      <td>0.626667</td>\n",
       "      <td>0.180975</td>\n",
       "      <td>713.000000</td>\n",
       "      <td>3662.000000</td>\n",
       "      <td>4548.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>548.500000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.655417</td>\n",
       "      <td>0.608602</td>\n",
       "      <td>0.730209</td>\n",
       "      <td>0.233214</td>\n",
       "      <td>1096.000000</td>\n",
       "      <td>4776.500000</td>\n",
       "      <td>5956.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>731.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.861667</td>\n",
       "      <td>0.840896</td>\n",
       "      <td>0.972500</td>\n",
       "      <td>0.507463</td>\n",
       "      <td>3410.000000</td>\n",
       "      <td>6946.000000</td>\n",
       "      <td>8714.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          instant      season          yr        mnth     holiday     weekday  \\\n",
       "count  731.000000  731.000000  731.000000  731.000000  731.000000  731.000000   \n",
       "mean   366.000000    2.496580    0.500684    6.519836    0.028728    2.997264   \n",
       "std    211.165812    1.110807    0.500342    3.451913    0.167155    2.004787   \n",
       "min      1.000000    1.000000    0.000000    1.000000    0.000000    0.000000   \n",
       "25%    183.500000    2.000000    0.000000    4.000000    0.000000    1.000000   \n",
       "50%    366.000000    3.000000    1.000000    7.000000    0.000000    3.000000   \n",
       "75%    548.500000    3.000000    1.000000   10.000000    0.000000    5.000000   \n",
       "max    731.000000    4.000000    1.000000   12.000000    1.000000    6.000000   \n",
       "\n",
       "       workingday  weathersit        temp       atemp         hum   windspeed  \\\n",
       "count  731.000000  731.000000  731.000000  731.000000  731.000000  731.000000   \n",
       "mean     0.683995    1.395349    0.495385    0.474354    0.627894    0.190486   \n",
       "std      0.465233    0.544894    0.183051    0.162961    0.142429    0.077498   \n",
       "min      0.000000    1.000000    0.059130    0.079070    0.000000    0.022392   \n",
       "25%      0.000000    1.000000    0.337083    0.337842    0.520000    0.134950   \n",
       "50%      1.000000    1.000000    0.498333    0.486733    0.626667    0.180975   \n",
       "75%      1.000000    2.000000    0.655417    0.608602    0.730209    0.233214   \n",
       "max      1.000000    3.000000    0.861667    0.840896    0.972500    0.507463   \n",
       "\n",
       "            casual   registered          cnt  \n",
       "count   731.000000   731.000000   731.000000  \n",
       "mean    848.176471  3656.172367  4504.348837  \n",
       "std     686.622488  1560.256377  1937.211452  \n",
       "min       2.000000    20.000000    22.000000  \n",
       "25%     315.500000  2497.000000  3152.000000  \n",
       "50%     713.000000  3662.000000  4548.000000  \n",
       "75%    1096.000000  4776.500000  5956.000000  \n",
       "max    3410.000000  6946.000000  8714.000000  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "season属性不同取值和出现的次数\n",
      "3    188\n",
      "2    184\n",
      "1    181\n",
      "4    178\n",
      "Name: season, dtype: int64\n",
      "\n",
      "mnth属性不同取值和出现的次数\n",
      "12    62\n",
      "10    62\n",
      "8     62\n",
      "7     62\n",
      "5     62\n",
      "3     62\n",
      "1     62\n",
      "11    60\n",
      "9     60\n",
      "6     60\n",
      "4     60\n",
      "2     57\n",
      "Name: mnth, dtype: int64\n",
      "\n",
      "weathersit属性不同取值和出现的次数\n",
      "1    463\n",
      "2    247\n",
      "3     21\n",
      "Name: weathersit, dtype: int64\n",
      "\n",
      "weekday属性不同取值和出现的次数\n",
      "6    105\n",
      "1    105\n",
      "0    105\n",
      "5    104\n",
      "4    104\n",
      "3    104\n",
      "2    104\n",
      "Name: weekday, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "#对类别型特征，观察其取值范围及直方图\n",
    "categorical_feature = [\"season\",\"mnth\",\"weathersit\",\"weekday\"]\n",
    "for col in categorical_feature:\n",
    "    print(\"\\n%s属性不同取值和出现的次数\"%col)\n",
    "    print(train[col].value_counts())\n",
    "    train[col] = train[col].astype(\"object\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7f48f2e40cc0>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f48efced6d8>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x7f48efc9f198>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f48efcc5c18>]],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#数值型特征分布\n",
    "numerical_feature = [\"temp\",\"atemp\",\"hum\",\"windspeed\"]\n",
    "train[numerical_feature].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f48efba9780>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sn.violinplot(data=train[[\"yr\",\"cnt\"]],x=\"yr\",y=\"cnt\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0.5,1,'dayly distribution of counts')]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import datetime\n",
    "train['date'] = pd.to_datetime(train[\"dteday\"])\n",
    "train['dayofyear'] = train[\"date\"].dt.dayofyear\n",
    "\n",
    "fig,ax = plt.subplots()\n",
    "sn.pointplot(data=train[[\"dayofyear\",\"cnt\",\"yr\"]],x=\"dayofyear\",y=\"cnt\",hue=\"yr\",ax=ax)\n",
    "ax.set(title=\"dayly distribution of counts\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f48eefd0400>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sn.violinplot(data=train[[\"season\",\"cnt\"]],x=\"season\",y=\"cnt\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0.5,1,'Seasonly distribution of counts')]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots()\n",
    "sn.barplot(data=train[[\"season\",\"cnt\"]],x=\"season\",y=\"cnt\")\n",
    "ax.set(title=\"Seasonly distribution of counts\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0.5,1,'monthly distribution of counts')]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots()\n",
    "sn.barplot(data=train[[\"mnth\",\"cnt\"]],x=\"mnth\",y=\"cnt\")\n",
    "ax.set(title=\"monthly distribution of counts\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f48eed244e0>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,(ax1,ax2) = plt.subplots(ncols = 2)\n",
    "sn.barplot(data=train,x=\"holiday\",y=\"cnt\",ax=ax1)\n",
    "sn.barplot(data=train,x=\"workingday\",y=\"cnt\",ax=ax2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f48eea1e470>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "corrMatt = train[[\"temp\",\"atemp\",\"hum\",\"windspeed\",\"casual\",\"registered\",\"cnt\"]].corr()\n",
    "mask = np.array(corrMatt)\n",
    "mask[np.tril_indices_from(mask)] = False\n",
    "sn.heatmap(corrMatt,mask=mask,vmax=.8,square=True,annot=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
